Abstract: A network device, including processing circuitry configured to determine a depth first search tree (DFST) based on a dependency graph included in a request to allocate memory bandwidth to a set of tasks, determine a set of groups of edges and nodes in the dependency graph based on the DFST, and allocate the memory bandwidth to the set of tasks by allocating the memory bandwidth to edges included in the set of groups of edges and nodes.

Abstract: A system for dynamic context automation workflow including a data center which includes an infrastructure and a configuration platform. The infrastructure includes physical resources for implementing at least one machine, and the configuration platform includes a configuration processor that coordinates automatic sequential execution of multiple tasks of a workflow by different agents each running on a different one of multiple contexts for updating a machine state controlled by the configuration processor.

Abstract: A scheduling application is used to acquire into memory of a first processing system running on a computer system, a first jobs load for execution by the first processing system, the first jobs load stored in a database's table and having a first load size, the database associated with the computer system. The scheduling application is used to acquire into memory of a second processing system, a second jobs load for execution by a second processing system. The second jobs load being included in the table and having a second load size being balanced with the first load size and including jobs not in the first jobs load. In the first processing system's memory, jobs in the first jobs load are scheduled for execution by the first processing system. In the second processing system's memory, jobs in the second jobs load are scheduled for execution by the second processing system.

Abstract: This disclosure describes techniques for providing virtual resources (e.g., containers, virtual machines, etc.) of a clustered application with information regarding a cluster of physical servers on which the distributed clustered application is running. A virtual resource that supports the clustered application is executed on a physical server of the cluster of physical servers. The virtual resource may receive an indication of a database instance (or other application) running on a particular physical server of the cluster of physical servers that is nearest the physical server. The database instance may be included in a group of database instances that are maintaining a common data set on respective physical servers of the group of physical servers. The virtual resource may then access the database instance on the particular physical server based at least in part on the database instance running on the particular server that is nearest the physical server.

Abstract: A method of operating a shared computing environment includes receiving a client request for an optimized runtime configuration of the shared computing environment for executing a task, receiving runtime data of the task collected from a prior runtime, inferring a runtime configuration from the runtime data, determining a predicted timeseries workload for the shared computing environment, updating the runtime configuration to including the timeseries workload prediction, wherein the updating outputs the optimized runtime configuration, and configuring the shared computing environment according to the optimized runtime configuration in executing the task.

Abstract: Methods for executing application programs in computer systems including a host computer formed of a plurality of servers configured to execute at least one virtual machine each hosting a primary user session associated to a remote client and at least one additional server may involve transmitting a primary session stream between the virtual machine and the remote client to emulate the presence, at the remote client, of a physical computer system. The execution of the application program may be initiated in a secondary user session hosted on the additional server and preparing a secondary session stream of the secondary user session. The primary and the secondary session streams may be aggregated to form an aggregated session stream, and the aggregated session stream may be processed at the remote client to emulate the execution of the application program on the physical computer system.

Abstract: Systems and methods for implementing single-click ejection of a mountable device associated with a virtual machine. An example method comprises: receiving, by a guest agent running on a virtual machine managed by a virtual machine manager (VMM) of a host computer system, a device removal request from the VMM, the device removal request identifying a peripheral device to be unmounted by the virtual machine; causing, by the guest agent, a guest operating system (OS) of the virtual machine to unmount the peripheral device; receiving, by the guest agent, a notification of completion of a device unmounting operation performed by the virtual machine with respect to the peripheral device; and transmitting, by the guest agent to the VMM, an operation completion status identified by the notification.

Abstract: Systems and methods for reliable flow measurement and control may include a processor having multiple cores. The compute device may further include circuitry configured to identify a time-critical software application to satisfy a target execution parameter for the measurement or control of fluid flow in an industrial environment. The circuitry may be further configured to allocate at least one resource of the compute device to execute the time-critical software application in satisfaction of the target execution parameter with at least one other software application in a single operating system, including dedicating a core of the processor to the execution of the time-critical software application. Additionally, the circuitry may be configured to execute the time-critical software application with the at least one other software application in the single operating system in satisfaction of the target execution parameter.

Abstract: The embodiments disclosed herein relate to using machine learning to allocate a number of concurrent processes for minimizing the completion time for executing a task having multiple subtasks. Historical data comprising a variety of subtask types with actual completion times is mined to create a set of statistical models for predicting completion time for a type of subtask. To minimize the total time to complete execution of a new task, a certain number of threads is allocated to execute subtasks of the new task. The certain number of threads is determined based on the predicted completion time for the subtasks using the respective statistical model. Threads are assigned to subtasks based on the predicted completion time for the subtasks, and the subtasks assigned to each thread are scheduled for execution.

Abstract: A set of workload criteria is determined from a workload associated with a plurality of sources. The workload is divided among a set of workload groups according to the set of workload criteria and a first workload scheduler. A set of edge computing resources is assigned to each workload group within the set according to the set of workload criteria and the set of workload groups. A portion of the workload associated with a subset of the plurality of sources is handled by a first subset of edge computing resources and a second workload scheduler, where the subset of sources is associated with a first workload group. The handling includes balancing, by the second workload scheduler, the portion of the workload among the subset of sources. The handled workload is reported to a control center.

Abstract: Migrating workloads between a plurality of execution environments, including: identifying, in dependence upon on characteristics of a workload, one or more execution environments that can support the workload; determining, for each execution environment, costs associated with supporting the workload on the execution environment; selecting, in dependence upon the costs associated with supporting the workload on each the execution environments, a target execution environment for supporting the workload; and executing the workload on the target execution environment.

Abstract: A network device includes a network interface, a host interface and processing circuitry. The network interface is configured to connect to a communication network. The host interface is configured to connect to a host including a processor. The processing circuitry is configured to receive from the processor, via the host interface, a notification specifying an operation for execution by the network device, the operation including (i) multiple tasks that are executable by the network device, and (ii) execution dependencies among the tasks in response to the notification, the processing circuitry is configured to determine a schedule for executing the tasks, the schedule complying with the execution dependencies, and to execute the operation by executing the tasks of the operation is accordance with the schedule.

Abstract: The present disclosure provides a computer system in which a virtual computer and a volume can be arranged in a cluster without degrading I/O performance of the virtual computer. A management node is configured to arrange a virtual computer and a volume in which the virtual computer inputs and outputs data in any one of a plurality of nodes, so as to allocate a predetermined resource among resources of a processor, a memory, and a storage drive to the virtual computer and the volume, thereby operating the virtual computer and the volume in the node. When the virtual computer and the volume can be arranged in the same node among the plurality of nodes, the management node determines the same node from the plurality of nodes based on a difference of ratios of resource amounts allocated to the virtual computer and the volume between the plurality of resources.

Abstract: A data storage apparatus includes a storage device; a controller to control data input and output operations of the storage device; and a swap memory provided in an outside of the controller, wherein the controller includes a thread manager to perform a preparation operation on a first thread included in a task in response to a request for processing the task, request the storage device to process the first thread on which the preparation operation has been performed, perform a preparation operation on at least one subsequent thread following the first thread while the storage device processes the first thread, and store context data of the first thread and the at least one subsequent thread in the swap memory, wherein the task includes the first thread and the at least one subsequent thread, and the preparation operation includes an address mapping operation.

Abstract: A queuing requester for access to a memory system is provided. Transaction requests are received from two or more requestors for access to the memory system. Each transaction request includes an associated priority value. A request queue of the received transaction requests is formed in the queuing requester. Each transaction request includes an associated priority value. A highest priority value of all pending transaction requests within the request queue is determined. An elevated priority value is selected when the highest priority value is higher than the priority value of an oldest transaction request in the request queue; otherwise the priority value of the oldest transaction request is selected. The oldest transaction request in the request queue with the selected priority value is then provided to the memory system. An arbitration contest with other requesters for access to the memory system is performed using the selected priority value.

Abstract: A system, computer program product, and method to deriving a cost model and dynamic adjustment of the derived model responsive to dynamic modification of one or more of the resources in a hybrid shared resource environment. Resources and corresponding configuration information are collected while monitoring runtime utilization of resource performance. As changes to the resources are discovered, the changes are subject to an assessment. A hybrid cost model is derived and configured to account for the one or more resources. The derived hybrid cost model is leveraged to conduct a multi-dimensional resource evaluation of the assessed changed configuration information. Responsive to the multi-dimensional evaluation, a generated resource utilization optimization of the one or more resources is selectively implemented.

Abstract: A message processing component may include an execution unit configurable to execute a set of tasks associated with one or more communication network messages. The set of tasks may include at least one of a message evaluation task or a cryptography task. The execution unit may be configured to provide functional safety in association with executing the set of tasks. The execution unit includes a set of time-multiplexed partitions. Each partition in the set of time-multiplexed partitions may be configurable to execute only one task included in the set of tasks. The message processing component may include an interface to one or more hardware accelerators available for use in association with the execution of the set of tasks. Only one partition, of the set of time-multiplexed partitions, may have access to the one or more hardware accelerators at a time.

Abstract: Disclosed are various implementations of approaches for reassigning hosts between computing clusters. A computing cluster assigned to a first queue is identified. The first queue can include a first list of identifiers of computing clusters with insufficient resources for a respective workload. A host machine assigned to a second queue can then be identified. The second queue can include a second list of identifiers of host machines in an idle state. A command can then be sent to the host machine to migrate to the computing cluster. Finally, the host machine can be removed from the second queue.

Abstract: This disclosure describes methods, devices, systems, and procedures in a computing system for capturing a configuration state of an operating system executing on a central processing unit (CPU), and offloading resource-related tasks, based on the configuration state, to a resource management unit such as a system-on-chip (SoC). The resource management unit identifies a status of each resource based on the captured configuration state of the operating system. The resource management unit then processes tasks associated with the status of the resources, such as modifying a clock rate of a clocked component in the computing system. This can alleviate the CPU from processing those tasks thereby improving overall computing system performance and dynamics.

Abstract: A method of remediating configurations of a plurality of system services running in each of a plurality of hosts, wherein each of the hosts is configured with a virtualization software for supporting execution of virtual machines therein, includes the steps of: retrieving actual configurations of the system services, wherein the actual configurations are stored in accordance with a configuration schema of the system services and include a user configuration, which is a configuration initiated by the user, and a system configuration, which is a configuration initiated by the host in response to the user configuration; retrieving desired configurations of the system services from a desired configuration file; comparing each of the actual configurations with a corresponding one of the desired configurations; and upon determining that at least one actual configuration, which is not a system configuration, is different from a corresponding one of the desired configurations, replacing the at least one actual config